《《eScholarship UC item 5nn455bt》.pdf

  1. 1、本文档共34页,可阅读全部内容。
  2. 2、有哪些信誉好的足球投注网站(book118)网站文档一经付费(服务费),不意味着购买了该文档的版权,仅供个人/单位学习、研究之用,不得用于商业用途,未经授权,严禁复制、发行、汇编、翻译或者网络传播等,侵权必究。
  3. 3、本站所有内容均由合作方或网友上传,本站不对文档的完整性、权威性及其观点立场正确性做任何保证或承诺!文档内容仅供研究参考,付费前请自行鉴别。如您付费,意味着您自己接受本站规则且自行承担风险,本站不退款、不进行额外附加服务;查看《如何避免下载的几个坑》。如果您已付费下载过本站文档,您可以点击 这里二次下载
  4. 4、如文档侵犯商业秘密、侵犯著作权、侵犯人身权等,请点击“版权申诉”(推荐),也可以打举报电话:400-050-0827(电话支持时间:9:00-18:30)。
查看更多
《《eScholarship UC item 5nn455bt》.pdf

Department of Statistics, UCLA UC Los Angeles Peer Reviewed Title: Image Parsing: Unifying Segmentation, Detection, and Recognition Author: Tu, Zhuowen Chen, Xiangrong Yuille, Alan Zhu, Song Chun Publication Date: 10-20-2005 Series: Department of Statistics Papers Publication Info: Department of Statistics Papers, Department of Statistics, UCLA, UC Los Angeles Permalink: /uc/item/5nn455bt eScholarship provides open access, scholarly publishing services to the University of California and delivers a dynamic research platform to scholars worldwide. Image Parsing: Unifying Segmentation, Detection, and Recognition Zhuowen Tu, Xiangrong Chen, Alan Yuille, and Song Chun Zhu Department of Statistics, UCLA. Los Angeles, CA 90095. USA {ztu,xrchen,yuille,sczhu}@ Abstract. In this chapter we present a Bayesian framework for pars- ing images into their constituent visual patterns. The parsing algorithm optimizes the posterior probability and outputs a scene representation as a “parsing graph”, in a spirit similar to parsing sentences in speech and natural language. The algorithm constructs the parsing graph and re-configures it dynamically using a set of moves, which are mostly re- versible Markov chain jumps. This computational framework integrates two popular inference approaches – generative (top-down) methods and discriminative (bottom-up) methods. The former formulates the pos- terior probability in terms of gen

文档评论(0)

qspd + 关注
实名认证
内容提供者

该用户很懒,什么也没介绍

1亿VIP精品文档

相关文档